Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

Citochromų P450 katalizuojamo vaistų metabolizmo kompiuterinis modeliavimas

The main objective of this study was the development of QSAR models for drug metabolism-related properties. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling method was used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. Models predicting CYP3A4 inhibition and regioselectivity of metabolism in human liver microsomes were developed and validated using external test sets. In all cases the baseline models already showed acceptable results, and the overall accuracy of predictions increased after the similarity based corrections. Moreover, the numbers of mispredictions reduced significantly when only results of higher reliability were taken into account. However, the original models are applicable only for less than a half of external datasets. Since the similarity correction procedure of GALAS modeling method allows simple model training, the possibility to expand the applicability domain has been tested. The CYP3A4 inhibition model was successfully adapted to PubChem data and compounds with a novel chemical scaffold. After training the regioselectivity model new metabolism sites could be identified in compounds of new chemical class. Moreover, this model was adapted for human cytochrome P450 isoform profiling

Computational modeling of cytochrome P450-mediated drug metabolism

The main objective of this study was the development of QSAR models for drug metabolism-related properties. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling method was used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. Models predicting CYP3A4 inhibition and regioselectivity of metabolism in human liver microsomes were developed and validated using external test sets. In all cases the baseline models already showed acceptable results, and the overall accuracy of predictions increased after the similarity based corrections. Moreover, the numbers of mispredictions reduced significantly when only results of higher reliability were taken into account. However, the original models are applicable only for less than a half of external datasets. Since the similarity correction procedure of GALAS modeling method allows simple model training, the possibility to expand the applicability domain has been tested. The CYP3A4 inhibition model was successfully adapted to PubChem data and compounds with a novel chemical scaffold. After training the regioselectivity model new metabolism sites could be identified in compounds of new chemical class. Moreover, this model was adapted for human cytochrome P450 isoform profiling

The COMER web server for protein analysis by homology

SUMMARY: Sequence homology is a basic concept in protein evolution, structure, and function studies. However, there are not many different tools and services for homology searches being sensitive, accurate, and fast at the same time. We present a new web server for protein analysis based on COMER2, a sequence alignment and homology search method that exhibits these characteristics. COMER2 has been upgraded since its last publication to improve its alignment quality and ease of use. We demonstrate how the user can benefit from using it by providing examples of extensive annotation of proteins of unknown function. Among the distinctive features of the web server is the user's ability to submit multiple queries with one click of a button. This and other features allow for transparently running homology searches-in a command-line, programmatic, or graphical environment-across multiple databases with multiple queries. They also promote extensive simultaneous protein analysis at the sequence, structure, and function levels. AVAILABILITY AND IMPLEMENTATION: The COMER web server is available at https://bioinformatics.lt/comer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction

The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template-based modeling and free docking. Structural templates were identified using sensitive sequence-based searches. If sequence-based searches failed, we performed structure-based template searches using selected CASP server models. In the absence of reliable templates we applied free docking starting from monomers generated by CASP servers. We evaluated and ranked models of protein complexes using an improved version of our protein structure quality assessment method, VoroMQA, taking into account both interaction interface and global structure scores. If reliable templates could be identified, generally accurate models of protein assemblies were generated with the exception of an antibody-antigen interaction. The success of free docking mainly depended on the accuracy of initial subunit models and on the scoring of docking solutions. To put our overall results in perspective, we analyzed our performance in the context of other CASP groups. Although the subunits in our assembly models often were not of the top quality, these models had, overall, the best-predicted intersubunit interfaces according to several accuracy measures. We attribute our relative success primarily to the emphasis on the interaction interface when modeling and scoring

Inferring the microscopic surface energy of protein-protein interfaces from mutation data

Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterised with empirical DDG values, yielding mean energies of -48 cal.mol−1.°A−2 for interactions between hydrophobic surfaces, -51 to -80 cal.mol−1.°A −2 for surfaces of complementary charge, and 66 to 83 cal.mol−1.°A−2 for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal.mol−1.°A−2. Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r=0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available opensource from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.This research was in part supported by postdoctoral fellowship funded by European Union Structural Funds project ”Postdoctoral Fellowship Implementation in Lithuania”. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Unions Seventh Framework Programme (FP7/2007-2013) under REA grant agreement PIEF-GA- 2012-327899, and the SpanishMinistry of Science and Innovation project [BIO2013- 48213-R]. The authors declare no conflict of interests.Peer Reviewe

Acetylcholine receptors at developing chick neuromuscular junctions

SIGLEAvailable from British Library Document Supply Centre- DSC:D34500/81 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Mapping of recognition sites of monoclonal antibodies responsible for the inhibition of pneumolysin functional activity

The pathogenicity of many bacteria, including Streptococcus pneumoniae, depends on pore-forming toxins (PFTs) that cause host cell lysis by forming large pores in cholesterol-containing cell membranes. Therefore, PFTs-neutralising antibodies may provide useful tools for reducing S. pneumoniae pathogenic effects. This study aimed at the development and characterisation of monoclonal antibodies (MAbs) with neutralising activity to S. pneumoniae PFT pneumolysin (PLY). Five out of 10 produced MAbs were able to neutralise the cytolytic activity of PLY on a lung epithelial cell line. Epitope mapping with a series of recombinant overlapping PLY fragments revealed that neutralising MAbs are directed against PLY loops L1 and L3 within domain 4. The epitopes of MAbs 3A9, 6E5 and 12F11 located at L1 loop (aa 454-471) were crucial for PLY binding to the immobilised cholesterol. In contrast, the MAb 12D10 recognising L3 (aa 403-423) and the MAb 3F3 against the conformational epitope did not interfere with PLY-cholesterol interaction. Due to conformation-dependent binding, the approach to use overlapping peptides for fine epitope mapping of the neutralising MAbs was unsuccessful. Therefore, the epitopes recognised by the MAbs were analysed using computational methods. This study provides new data on PLY sites involved in functional activity

SKEMPI 2.0: an updated benchmark of changes in protein¿protein binding energy, kinetics and thermodynamics upon mutation

[Motivation]: Understanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein–protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering.[Results]: We present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein–protein interactions. This version now contains manually curated binding data for 7085 mutations, an increase of 133%, including changes in kinetics for 1844 mutations, enthalpy and entropy changes for 443 mutations, and 440 mutations, which abolish detectable binding.This work has been supported by the European Molecular Biology Laboratory [I.H.M.]; Biotechnology and Biological Sciences Research Council [Future Leader Fellowship BB/N011600/1 to I.H.M.]; Spanish Ministry of Economy and Competitiveness (MINECO) [BIO2016-79930-R to J.F.R.]; Interreg POCTEFA [EFA086/15 to J.F.R.]; European Commission [H2020 grant 676566 (MuG)]

PIGN-Related Disease in Two Lithuanian Families: A Report of Two Novel Pathogenic Variants, Molecular and Clinical Characterisation

Background and Objectives: Pathogenic variants of PIGN are a known cause of multiple congenital anomalies-hypotonia-seizures syndrome 1 (MCAHS1). Many affected individuals have clinical features overlapping with Fryns syndrome and are mainly characterised by developmental delay, congenital anomalies, hypotonia, seizures, and specific minor facial anomalies. This study investigates the clinical and molecular data of three individuals from two unrelated families, the clinical features of which were consistent with a diagnosis of MCAHS1. Materials and Methods: Next-generation sequencing (NGS) technology was used to identify the changes in the DNA sequence. Sanger sequencing of gDNA of probands and their parents was used for validation and segregation analysis. Bioinformatics tools were used to investigate the consequences of pathogenic or likely pathogenic PIGN variants at the protein sequence and structure level. Results: The analysis of NGS data and segregation analysis revealed a compound heterozygous NM_176787.5:c.[1942G>T];[1247_1251del] PIGN genotype in family 1 and NG_033144.1(NM_176787.5):c.[932T>G];[1674+1G>C] PIGN genotype in family 2. In silico, c.1942G>T (p.(Glu648Ter)), c.1247_1251del (p.(Glu416GlyfsTer22)), and c.1674+1G>C (p.(Glu525AspfsTer68)) variants are predicted to result in a premature termination codon that leads to truncated and functionally disrupted protein causing the phenotype of MCAHS1 in the affected individuals. Conclusions: PIGN-related disease represents a wide spectrum of phenotypic features, making clinical diagnosis inaccurate and complicated. The genetic testing of every individual with this phenotype provides new insights into the origin and development of the disease